Partitioning and mapping workloads for scalable SaaS applications on cloud
A system for migrating a non-tenant-aware local application to a tenant-aware cloud application environment is disclosed to migrate individual modules of the application to instances of the cloud by grouping the modules via common characteristics in partition groups. By grouping modules together by partition group before migrating the modules to cloud instances, modules that share resources can be placed in closer logical proximity to one another in the cloud to optimize performance.
1. A method for configuring workloads, comprising:
identifying workloads of a non-tenant-aware application and a set of application characteristics for each of the identified workloads;
creating a partition of the workloads in reference to a partition application characteristic;
grouping the created partition of the workloads into a plurality of workload sub-partitions as a function of a common workload characteristic;
assigning each partition of the workloads to a set of cloud resources as a function of the partition application characteristic and a characteristic of the set of cloud resources;
constructing a plurality of workload assignment maps to assign to each of the workloads in accordance with the created partition, and
ranking each one of plurality of workload assignment maps based on a set of rules.
2. The method of claim 1 wherein is the set of application characteristics is selected from the group consisting of software components, software dependencies, hardware dependencies, and application environment contexts.
3. The method of claim 2 wherein the set of application characteristics is selected from the group consisting of hardware characteristics, software characteristics, and network characteristics.
4. The method of claim 1 wherein the characteristic of the set of cloud resources is selected from the group consisting of hardware characteristics, software characteristics, and network characteristics.
5. The method of claim 1 wherein the set of rules comprise a permutation desirability metric for a workload assignment map, a user cost metric, a user efficiency metric, a security metric and a scalability metric.